Search results for: precision farming
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1485

Search results for: precision farming

975 Options for Adding Benefits of Local Crop Diversity Through a Non-Breeding Approach

Authors: Kedar Nath Nepal, Tek Bahadur Thapa, David Guerena;

Abstract:

The community participation is central to the in-situ project objectives, as farming communities are key stakeholders in the on-farm conservation of agricultural bio- diversity. Besides technical means to adding benefits, the complimentary strategy includes creating market-based value adding measures by increasing users’ awareness of the value of traditional foods and nutritional values; exhibitions and improved processing; and policy incentives. This paper presents various participatory activities carried out in Nepal as options for enhancing benefits to local communities by increased utilization of local crop diversity on -the farm through non-breeding discussed, and outcomes are documented using farmers’ perception data and secondary information. The paper focuses on three major areas of public awareness, market incentives and non-market incentives that may enhance on -farm conservation and use of biodiversity.

Keywords: biodiversity, in-situ, market-based, non-market

Procedia PDF Downloads 99
974 Friction Estimation and Compensation for Steering Angle Control for Highly Automated Driving

Authors: Marcus Walter, Norbert Nitzsche, Dirk Odenthal, Steffen Müller

Abstract:

This contribution presents a friction estimator for industrial purposes which identifies Coulomb friction in a steering system. The estimator only needs a few, usually known, steering system parameters. Friction occurs on almost every mechanical system and has a negative influence on high-precision position control. This is demonstrated on a steering angle controller for highly automated driving. In this steering system the friction induces limit cycles which cause oscillating vehicle movement when the vehicle follows a given reference trajectory. When compensating the friction with the introduced estimator, limit cycles can be suppressed. This is demonstrated by measurements in a series vehicle.

Keywords: friction estimation, friction compensation, steering system, lateral vehicle guidance

Procedia PDF Downloads 499
973 Secure Image Retrieval Based on Orthogonal Decomposition under Cloud Environment

Authors: Y. Xu, L. Xiong, Z. Xu

Abstract:

In order to protect data privacy, image with sensitive or private information needs to be encrypted before being outsourced to the cloud. However, this causes difficulties in image retrieval and data management. A secure image retrieval method based on orthogonal decomposition is proposed in the paper. The image is divided into two different components, for which encryption and feature extraction are executed separately. As a result, cloud server can extract features from an encrypted image directly and compare them with the features of the queried images, so that the user can thus obtain the image. Different from other methods, the proposed method has no special requirements to encryption algorithms. Experimental results prove that the proposed method can achieve better security and better retrieval precision.

Keywords: secure image retrieval, secure search, orthogonal decomposition, secure cloud computing

Procedia PDF Downloads 471
972 Fast Algorithm to Determine Initial Tsunami Wave Shape at Source

Authors: Alexander P. Vazhenin, Mikhail M. Lavrentiev, Alexey A. Romanenko, Pavel V. Tatarintsev

Abstract:

One of the problems obstructing effective tsunami modelling is the lack of information about initial wave shape at source. The existing methods; geological, sea radars, satellite images, contain an important part of uncertainty. Therefore, direct measurement of tsunami waves obtained at the deep water bottom peruse recorders is also used. In this paper we propose a new method to reconstruct the initial sea surface displacement at tsunami source by the measured signal (marigram) approximation with the help of linear combination of synthetic marigrams from the selected set of unit sources, calculated in advance. This method has demonstrated good precision and very high performance. The mathematical model and results of numerical tests are here described.

Keywords: numerical tests, orthogonal decomposition, Tsunami Initial Sea Surface Displacement

Procedia PDF Downloads 455
971 Introduction of Microbial Symbiosis in Genus of Tridacna and Kiwaidae with Insights into Aquaculture

Authors: Jincao Guo

Abstract:

Aquaculture plays a significant role in the diet of people in many regions. However, problems such as bioaccumulation have risen with the rapidly growing industry due to a lack of control in the feeding process, which brings uncertainty to the quality of the products. The paper tackles the problem by introducing the symbiosis of the Giant Clam (Tridacna) with photosynthetic algae and Yeti Crab (Kiwaidae) with chemosynthetic bacteria in molecular and developmental details. By combing the knowledge gained from the two models and past studies, innovative ideas such as using mass selection methods to domesticate and farm those symbiotic species, as well as improvements for the current farming methods, such as introducing algae feeding, are discussed. Further studies are needed, but experiments are worth conducting since it increases the variety of choices for consumers and can potentially improve the quality and efficiency of aquaculture.

Keywords: the giant clam Tridacna, yeti crab Kiwaidae, autotroph microbes, microbial symbiosis, aquaculture, bivalves, crustaceans, mollusk, photosynthesis, chemosynthesis

Procedia PDF Downloads 61
970 Estimation of Soil Nutrient Content Using Google Earth and Pleiades Satellite Imagery for Small Farms

Authors: Lucas Barbosa Da Silva, Jun Okamoto Jr.

Abstract:

Precision Agriculture has long being benefited from crop fields’ aerial imagery. This important tool has allowed identifying patterns in crop fields, generating useful information to the production management. Reflectance intensity data in different ranges from the electromagnetic spectrum may indicate presence or absence of nutrients in the soil of an area. Different relations between the different light bands may generate even more detailed information. The knowledge of the nutrients content in the soil or in the crop during its growth is a valuable asset to the farmer that seeks to optimize its yield. However, small farmers in Brazil often lack the resources to access this kind information, and, even when they do, it is not presented in a comprehensive and/or objective way. So, the challenges of implementing this technology ranges from the sampling of the imagery, using aerial platforms, building of a mosaic with the images to cover the entire crop field, extracting the reflectance information from it and analyzing its relationship with the parameters of interest, to the display of the results in a manner that the farmer may take the necessary decisions more objectively. In this work, it’s proposed an analysis of soil nutrient contents based on image processing of satellite imagery and comparing its outtakes with commercial laboratory’s chemical analysis. Also, sources of satellite imagery are compared, to assess the feasibility of using Google Earth data in this application, and the impacts of doing so, versus the application of imagery from satellites like Landsat-8 and Pleiades. Furthermore, an algorithm for building mosaics is implemented using Google Earth imagery and finally, the possibility of using unmanned aerial vehicles is analyzed. From the data obtained, some soil parameters are estimated, namely, the content of Potassium, Phosphorus, Boron, Manganese, among others. The suitability of Google Earth Imagery for this application is verified within a reasonable margin, when compared to Pleiades Satellite imagery and to the current commercial model. It is also verified that the mosaic construction method has little or no influence on the estimation results. Variability maps are created over the covered area and the impacts of the image resolution and sample time frame are discussed, allowing easy assessments of the results. The final results show that easy and cheaper remote sensing and analysis methods are possible and feasible alternatives for the small farmer, with little access to technological and/or financial resources, to make more accurate decisions about soil nutrient management.

Keywords: remote sensing, precision agriculture, mosaic, soil, nutrient content, satellite imagery, aerial imagery

Procedia PDF Downloads 162
969 Sustainable Food Systems in Community Development: Integrating Urban Food Security into a Growing Population

Authors: Opal Giulianelli, Pegah Zamani

Abstract:

Sustainable food has become a frequently debated topic in recent years due to a consumer push for environmentally sustainable food. While some research works on improving the monoculture farm systems that are currently in use, others focus on expanding the definition of sustainable food systems. This research looks at those concepts of alternative food systems applied to a more extensive city system. The goal is to create a theoretical site plan that could be implemented in emerging cities and other urban environments. This site plan combines the ideas of environmentally sustainable food development, such as food forests, urban farming, and community gardens. This would represent one part of a larger sustainable food system that can be altered depending on the environment or the people it is serving. However, this research is being carried out with the southeast United States in mind and, therefore, may prove difficult to apply to other regions, especially those of radically different climates.

Keywords: alternative food systems, urban design, food forests, aquaponics, hydroponics, food security, food system design

Procedia PDF Downloads 87
968 The Influence of a Radio Intervention on Farmers’ Practices in Climate Change Mitigation and Adaptation in Kilifi, Kenya

Authors: Fiona Mwaniki

Abstract:

Climate change is considered a serious threat to sustainable development globally and as one of the greatest ecological, economic and social challenges of our time. The global demand for food is projected to increase by 60% by 2050. Small holder farmers who are vulnerable to the adverse effects of climate change are expected to contribute to this projected demand. Effective climate change education and communication is therefore required for smallholder and subsistence farmers’ in order to build communities that are more climate change aware, prepared and resilient. In Kenya radio is the most important and dominant mass communication tool for agricultural extension. This study investigated the potential role of radio in influencing farmers’ understanding and use of climate change information. The broad aims of this study were three-fold. Firstly, to identify Kenyan farmers’ perceptions and responses to the impacts of climate change. Secondly, to develop radio programs that communicate climate change information to Kenyan farmers and thirdly, to evaluate the impact of information disseminated through radio on farmers’ understanding and responses to climate change mitigation and adaptation. This study was conducted within the farming community of Kilifi County, located along the Kenyan coast. Education and communication about climate change was undertaken using radio to make available information understandable to different social and cultural groups. A mixed methods pre-and post-intervention design that provided the opportunity for triangulating results from both quantitative and qualitative data was used. Quantitative and qualitative data was collected simultaneously, where quantitative data was collected through semi structured surveys with 421 farmers’ and qualitative data was derived from 11 focus group interviews, six interviews with key informants and nine climate change experts. The climate change knowledge gaps identified in the initial quantitative and qualitative data were used in developing radio programs. Final quantitative and qualitative data collection and analysis enabled an assessment of the impact of climate change messages aired through radio on the farming community in Kilifi County. Results of this study indicate that 32% of the farmers’ listened to the radio programs and 26% implemented technologies aired on the programs that would help them adapt to climate change. The most adopted technologies were planting drought tolerant crops including indigenous crop varieties, planting trees, water harvesting and use of manure. The proportion of farmers who indicated they knew “a fair amount” about climate change increased significantly (Z= -5.1977, p < 0.001) from 33% (at the pre intervention phase of this study) to 64% (post intervention). However, 68% of the farmers felt they needed “a lot more” information on agriculture interventions (43%), access to financial resources (21%) and the effects of climate change (15%). The challenges farmers’ faced when adopting the interventions included lack of access to financial resources (18%), high cost of adaptation measures (17%), and poor access to water (10%). This study concludes that radio effectively complements other agricultural extension methods and has the potential to engage farmers’ on climate change issues and motivate them to take action.

Keywords: climate change, climate change intervention, farmers, radio

Procedia PDF Downloads 329
967 A New Evolutionary Algorithm for Multi-Objective Cylindrical Spur Gear Design Optimization

Authors: Hammoudi Abderazek

Abstract:

The present paper introduces a modified adaptive mixed differential evolution (MAMDE) to select the main geometry parameters of specific cylindrical spur gear. The developed algorithm used the self-adaptive mechanism in order to update the values of mutation and crossover factors. The feasibility rules are used in the selection phase to improve the search exploration of MAMDE. Moreover, the elitism is performed to keep the best individual found in each generation. For the constraints handling the normalization method is used to treat each constraint design equally. The finite element analysis is used to confirm the optimization results for the maximum bending resistance. The simulation results reached in this paper indicate clearly that the proposed algorithm is very competitive in precision gear design optimization.

Keywords: evolutionary algorithm, spur gear, tooth profile, meta-heuristics

Procedia PDF Downloads 120
966 On-Farm Mechanized Conservation Agriculture: Preliminary Agro-Economic Performance Difference between Disc Harrowing, Ripping and No-Till

Authors: Godfrey Omulo, Regina Birner, Karlheinz Koller, Thomas Daum

Abstract:

Conservation agriculture (CA) as a climate-resilient and sustainable practice have been carried out for over three decades in Zambia. However, its continued promotion and adoption has been predominantly on a small-scale basis. Despite the plethora of scholarship pointing to the positive benefits of CA in regard to enhanced yield, profitability, carbon sequestration and minimal environmental degradation, these have not stimulated commensurate agricultural extensification desired for Zambia. The objective of this study was to investigate the potential differences between mechanized conventional and conservation tillage practices on operation time, fuel consumption, labor costs, soil moisture retention, soil temperature and crop yield. An on-farm mechanized conservation agriculture (MCA) experiment arranged in a randomized complete block design with four replications was used. The research was conducted on a 15 ha of sandy loam rainfed land: soybeans on 7ha with plot dimensions of 24 m by 210 m and maize on 8ha with plot dimensions of 24 m by 250 m. The three tillage treatments were: residue burning followed by disc harrowing, ripping tillage and no-till. The crops were rotated in two subsequent seasons. All operations were done using a 60hp 2-wheel tractor, a disc harrow, a two-tine ripper and a two-row planter. Soil measurements and the agro-economic factors were recorded for two farming seasons. The season results showed that the yield of maize and soybeans under no-till and ripping tillage practices were not significantly different from the conventional burning and discing. But, there was a significant difference in soil moisture content between no-till (25.31SFU±2.77) and disced (11.91SFU±0.59) plots at depths from 10-60 cm. Soil temperature in no-till plots (24.59°C±0.91) was significantly lower compared to the disced plots (26.20°C±1.75) at the depths 15 cm and 45 cm. For maize, there was a significant difference in operation time between disc-harrowed (3.68hr/ha±1.27) and no-till (1.85hr/ha±0.04) plots, and a significant difference in cost of labor between disc-harrowed (45.45$/ha±19.56) and no-till (21.76$/ha) plots. There was no significant difference in fuel consumption between ripping and disc-harrowing and direct seeding. For soybeans, there was a significant difference in operation time between no-tillage (1.96hr/ha±0.31) and ripping (3.34hr/ha±0.53) and disc harrowing (3.30hr/ha±0.16). Further, fuel consumption and labor on no-till plots were significantly different from both the ripped and disc-harrowed plots. The high seed emergence percentage on maize disc-harrowed plot (93.75%±5.87) was not significantly different from ripping and no-till plots. Again, the high seed emergence percentage for the soybean ripped plot (93.75%±13.03) had no significant difference with discing and ripping. The results show that it is economically sound and timesaving to practice MCA and get viable yields compared to conventional farming. This research fills the gap on the potential of MCA in the context of Zambia and its profitability in incentivizing policymakers to invest in appropriate and sustainable machinery and implements for extensive agricultural production.

Keywords: climate-smart agriculture, labor cost, mechanized conservation agriculture, soil moisture, Zambia

Procedia PDF Downloads 138
965 Biodiversity and Biotechnology: Some Considerations about the International Regulation of Agriculture and the International Legal System on Access to Genetic Resources

Authors: Leandro Moura da Silva

Abstract:

The international community has strived to create legal mechanisms to protect their biodiversity, but this can represent, sometimes, particularly in the case of regulatory regime on access to genetic resources, an excessive nationalism which transforms itself into a significant obstacle to scientific progress causing damages to the country and to local farmers. Although it has been poorly publicized in the media, the international legal system was marked, in 2014, by the entry into force of the Nagoya Protocol, which regulates the access and benefit sharing of genetic resources of the States Party to that legal instrument. However, it’s not reasonable to think of regulating access to genetic resources without reflecting on the links of this important subject with other related issues, such as family farming and agribusiness, food safety, food security, intellectual property rights (on seeds, genetic material, new plant varieties, etc.), environmental sustainability, biodiversity, and biosafety.

Keywords: international law, regulation on agriculture, agronomy techniques, sustainability, genetic resources and new crop varieties, CBD, Nagoya Protocol, ITPGRFA

Procedia PDF Downloads 492
964 Predicting Groundwater Areas Using Data Mining Techniques: Groundwater in Jordan as Case Study

Authors: Faisal Aburub, Wael Hadi

Abstract:

Data mining is the process of extracting useful or hidden information from a large database. Extracted information can be used to discover relationships among features, where data objects are grouped according to logical relationships; or to predict unseen objects to one of the predefined groups. In this paper, we aim to investigate four well-known data mining algorithms in order to predict groundwater areas in Jordan. These algorithms are Support Vector Machines (SVMs), Naïve Bayes (NB), K-Nearest Neighbor (kNN) and Classification Based on Association Rule (CBA). The experimental results indicate that the SVMs algorithm outperformed other algorithms in terms of classification accuracy, precision and F1 evaluation measures using the datasets of groundwater areas that were collected from Jordanian Ministry of Water and Irrigation.

Keywords: classification, data mining, evaluation measures, groundwater

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963 Model Predictive Control (MPC) and Proportional-Integral-Derivative (PID) Control of Quadcopters: A Comparative Analysis

Authors: Anel Hasić, Naser Prljača

Abstract:

In the domain of autonomous or piloted flights, the accurate control of quadrotor trajectories is of paramount significance for large numbers of tasks. These adaptable aerial platforms find applications that span from high-precision aerial photography and surveillance to demanding search and rescue missions. Among the fundamental challenges confronting quadrotor operation is the demand for accurate following of desired flight paths. To address this control challenge, among others, two celebrated well-established control strategies have emerged as noteworthy contenders: Model Predictive Control (MPC) and Proportional-Integral-Derivative (PID) control. In this work, we focus on the extensive examination of MPC and PID control techniques by using comprehensive simulation studies in MATLAB/Simulink. Intensive simulation results demonstrate the performance of the studied control algorithms.

Keywords: MATLAB, MPC, PID, quadcopter, simulink

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962 Two-Dimensional WO₃ and TiO₂ Semiconductor Oxides Developed by Atomic Layer Deposition with Controllable Nano-Thickness on Wafer-Scale

Authors: S. Zhuiykov, Z. Wei

Abstract:

Conformal defect-free two-dimensional (2D) WO₃ and TiO₂ semiconductors have been developed by the atomic layer deposition (ALD) technique on wafer scale with unique approach to the thickness control with precision of ± 10% from the monolayer of nanomaterial (less than 1.0 nm thick) to the nano-layered 2D structures with thickness of ~3.0-7.0 nm. Developed 2D nanostructures exhibited unique, distinguishable properties at nanoscale compare to their thicker counterparts. Specifically, 2D TiO₂-Au bilayer demonstrated improved photocatalytic degradation of palmitic acid under UV and visible light illumination. Improved functional capabilities of 2D semiconductors would be advantageous to various environmental, nano-energy and bio-sensing applications. The ALD-enabled approach is proven to be versatile, scalable and applicable to the broader range of 2D semiconductors.

Keywords: two-dimensional (2D) semiconductors, ALD, WO₃, TiO₂, wafer scale

Procedia PDF Downloads 143
961 Standard and Processing of Photodegradable Polyethylene

Authors: Nurul-Akidah M. Yusak, Rahmah Mohamed, Noor Zuhaira Abd Aziz

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The introduction of degradable plastic materials into agricultural sectors has represented a promising alternative to promote green agriculture and environmental friendly of modern farming practices. Major challenges of developing degradable agricultural films are to identify the most feasible types of degradation mechanisms, composition of degradable polymers and related processing techniques. The incorrect choice of degradable mechanisms to be applied during the degradation process will cause premature losses of mechanical performance and strength. In order to achieve controlled process of agricultural film degradation, the compositions of degradable agricultural film also important in order to stimulate degradation reaction at required interval of time and to achieve sustainability of the modern agricultural practices. A set of photodegradable polyethylene based agricultural film was developed and produced, following the selective optimization of processing parameters of the agricultural film manufacturing system. Example of agricultural films application for oil palm seedlings cultivation is presented.

Keywords: photodegradable polyethylene, plasticulture, processing schemes

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960 Calibration of the Radical Installation Limit Error of the Accelerometer in the Gravity Gradient Instrument

Authors: Danni Cong, Meiping Wu, Xiaofeng He, Junxiang Lian, Juliang Cao, Shaokuncai, Hao Qin

Abstract:

Gravity gradient instrument (GGI) is the core of the gravity gradiometer, so the structural error of the sensor has a great impact on the measurement results. In order not to affect the aimed measurement accuracy, limit error is required in the installation of the accelerometer. In this paper, based on the established measuring principle model, the radial installation limit error is calibrated, which is taken as an example to provide a method to calculate the other limit error of the installation under the premise of ensuring the accuracy of the measurement result. This method provides the idea for deriving the limit error of the geometry structure of the sensor, laying the foundation for the mechanical precision design and physical design.

Keywords: gravity gradient sensor, radial installation limit error, accelerometer, uniaxial rotational modulation

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959 Evaluation of Photovoltaic System with Different Research Methods of Maximum Power Point Tracking

Authors: Mehdi Ameur, Ahmed Essadki, Tamou Nasser

Abstract:

The purpose of this paper is the evaluation of photovoltaic system with MPPT techniques. This system is developed by combining the models of established solar module and DC-DC converter with the algorithms of perturbing and observing (P&O), incremental conductance (INC) and fuzzy logic controller (FLC). The system is simulated under different climate conditions and MPPT algorithms to determine the influence of these conditions on characteristic power-voltage of PV system. According to the comparisons of the simulation results, the photovoltaic system can extract the maximum power with precision and rapidity using the MPPT algorithms discussed in this paper.

Keywords: fuzzy logic controller, FLC, hill climbing, HC, incremental conductance (INC), perturb and observe (P&O), maximum power point, MPP, maximum power point tracking, MPPT

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958 A Laser Instrument Rapid-E+ for Real-Time Measurements of Airborne Bioaerosols Such as Bacteria, Fungi, and Pollen

Authors: Minghui Zhang, Sirine Fkaier, Sabri Fernana, Svetlana Kiseleva, Denis Kiselev

Abstract:

The real-time identification of bacteria and fungi is difficult because they emit much weaker signals than pollen. In 2020, Plair developed Rapid-E+, which extends abilities of Rapid-E to detect smaller bioaerosols such as bacteria and fungal spores with diameters down to 0.3 µm, while keeping the similar or even better capability for measurements of large bioaerosols like pollen. Rapid-E+ enables simultaneous measurements of (1) time-resolved, polarization and angle dependent Mie scattering patterns, (2) fluorescence spectra resolved in 16 channels, and (3) fluorescence lifetime of individual particles. Moreover, (4) it provides 2D Mie scattering images which give the full information on particle morphology. The parameters of every single bioaerosol aspired into the instrument are subsequently analysed by machine learning. Firstly, pure species of microbes, e.g., Bacillus subtilis (a species of bacteria), and Penicillium chrysogenum (a species of fungal spores), were aerosolized in a bioaerosol chamber for Rapid-E+ training. Afterwards, we tested microbes under different concentrations. We used several steps of data analysis to classify and identify microbes. All single particles were analysed by the parameters of light scattering and fluorescence in the following steps. (1) They were treated with a smart filter block to get rid of non-microbes. (2) By classification algorithm, we verified the filtered particles were microbes based on the calibration data. (3) The probability threshold (defined by the user) step provides the probability of being microbes ranging from 0 to 100%. We demonstrate how Rapid-E+ identified simultaneously microbes based on the results of Bacillus subtilis (bacteria) and Penicillium chrysogenum (fungal spores). By using machine learning, Rapid-E+ achieved identification precision of 99% against the background. The further classification suggests the precision of 87% and 89% for Bacillus subtilis and Penicillium chrysogenum, respectively. The developed algorithm was subsequently used to evaluate the performance of microbe classification and quantification in real-time. The bacteria and fungi were aerosolized again in the chamber with different concentrations. Rapid-E+ can classify different types of microbes and then quantify them in real-time. Rapid-E+ enables classifying different types of microbes and quantifying them in real-time. Rapid-E+ can identify pollen down to species with similar or even better performance than the previous version (Rapid-E). Therefore, Rapid-E+ is an all-in-one instrument which classifies and quantifies not only pollen, but also bacteria and fungi. Based on the machine learning platform, the user can further develop proprietary algorithms for specific microbes (e.g., virus aerosols) and other aerosols (e.g., combustion-related particles that contain polycyclic aromatic hydrocarbons).

Keywords: bioaerosols, laser-induced fluorescence, Mie-scattering, microorganisms

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957 Impact of Improved Beehive on Income of Rural Households: Evidence from Bugina District of Northern Ethiopia

Authors: Wondmnew Derebe

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Increased adoption of modern beehives improves the livelihood of smallholder farmers whose income largely depends on mixed crop-livestock farming. Improved beehives have been disseminated to farmers in many parts of Ethiopia. However, its impact on income is less investigated. Thus, this study estimates how adopting improved beehives impacts rural households' income. Survey data were collected from 350 randomly selected households' and analyzed using an endogenous switching regression model. The result revealed that the adoption of improved beehives is associated with a higher annual income. On average, improved beehive adopters earned about 6,077 (ETB) more money than their counterparts. However, the impact of adoption would have been larger for actual non-adopters, as reflected in the negative transitional heterogeneity effect of 1792 (ETB). The result also indicated that the decision to adopt or not to adopt improved beehives was subjected to individual self-selection. Improved beehive adoption can increase farmers' income and can be used as an alternative poverty reduction strategy.

Keywords: impact, adoption, endogenous switching regression, income, improved

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956 Experimental Studies on the Effect of Rake Angle on Turning Ti-6Al-4V with TiAlN Coated Carbides

Authors: Satyanarayana Kosaraju, Venu Gopal Anne, Sateesh Nagari

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In this paper, the effect of cutting speed, feedrate and rake angle in tool geometry on cutting forces and temperature generated on the tool tip in turning were investigated. The data used for the investigation derived from experiments conducted on precision lathe according to the full factorial design to observe the effect of each factor level on the process performance. During the tests, depth of cut were kept constant and each test was conducted with a sharp coated tool insert. Ti-6Al-4V was used as the workpiece material. The effects of cutting parameters and tool geometry on cutting forces and tool tip temperature were analyzed. The main cutting force was observed to have a decreasing trend and temperature found to be increasing trend as the rake angle increased.

Keywords: cutting force, tool tip temperature, rake angle, machining

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955 SEM-EBSD Observation for Microtubes by Using Dieless Drawing Process

Authors: Takashi Sakai, Itaru Kumisawa

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Because die drawing requires insertion of a die, a plug, or a mandrel, higher precision and efficiency are demanded for drawing equipment for a tube having smaller diameter. Manufacturing of such tubes is also accompanied by problems such as cracking and fracture. We specifically examine dieless drawing, which is less affected by these drawing-related difficulties. This deformation process is governed by a similar principle to that of reduction in diameter when pulling a heated glass tube. We conducted dieless drawing of SUS304 stainless steel microtubes under various conditions with three factor parameters of heating temperature, area reduction, and drawing speed. We used SEM-EBSD to observe the processing condition effects on microstructural elements. As the result of this study, crystallographic orientation of microtube is clear by using SEM-EBSD analysis.

Keywords: microtube, dieless drawing, IPF (inverse pole figure), GOS (grain orientation spread), crystallographic analysis

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954 Object Recognition Approach Based on Generalized Hough Transform and Color Distribution Serving in Generating Arabic Sentences

Authors: Nada Farhani, Naim Terbeh, Mounir Zrigui

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The recognition of the objects contained in images has always presented a challenge in the field of research because of several difficulties that the researcher can envisage because of the variability of shape, position, contrast of objects, etc. In this paper, we will be interested in the recognition of objects. The classical Hough Transform (HT) presented a tool for detecting straight line segments in images. The technique of HT has been generalized (GHT) for the detection of arbitrary forms. With GHT, the forms sought are not necessarily defined analytically but rather by a particular silhouette. For more precision, we proposed to combine the results from the GHT with the results from a calculation of similarity between the histograms and the spatiograms of the images. The main purpose of our work is to use the concepts from recognition to generate sentences in Arabic that summarize the content of the image.

Keywords: recognition of shape, generalized hough transformation, histogram, spatiogram, learning

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953 Knowledge and Adoption of Agricultural Biotechnology among Small-Scale Farmers in Taraba State Nigeria

Authors: A. H. Paul, L. J. Gizaki, E. P. Ejimbi

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The study was carried out to determine the level of knowledge and adoption of agricultural biotechnology in Taraba state. Purposive and simple sampling techniques were used to select respondents. Questionnaires were administered to 90 respondents. Data were analyzed using descriptive and inferential statistics. The results showed that the majority (73.3%) of the respondents were small-scale farmers, whereas 24.4 percent were engaged in secondary occupations. The mean farm size was 1-5 ha. The majority (72.2%) had one form of formal education or another. About 84 percent (84.4%) had been farming for at least 10 years. There was a mean household size of 6-10 persons. Many (97.8%) of the respondents were knowledgeable about biotechnology, and about 70.0 percent (70.1%) reported that the biotechnology products which they had adopted were very good for animals and human consumption. The result of Pearson’s correlation (r = 0.699) was significant at the 0.01 alpha level. Therefore, the hypothesis that there is no significant relationship between knowledge and adoption of agricultural biotechnology was rejected. It was concluded that the agricultural biotechnologies that were adopted were very safe for animals, humans, and the environment. It was recommended that the government should employ more extension agents to help educate farmers about agricultural biotechnology.

Keywords: agricultural, adoption, biotechnology, knowledge

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952 Multidimensional Item Response Theory Models for Practical Application in Large Tests Designed to Measure Multiple Constructs

Authors: Maria Fernanda Ordoñez Martinez, Alvaro Mauricio Montenegro

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This work presents a statistical methodology for measuring and founding constructs in Latent Semantic Analysis. This approach uses the qualities of Factor Analysis in binary data with interpretations present on Item Response Theory. More precisely, we propose initially reducing dimensionality with specific use of Principal Component Analysis for the linguistic data and then, producing axes of groups made from a clustering analysis of the semantic data. This approach allows the user to give meaning to previous clusters and found the real latent structure presented by data. The methodology is applied in a set of real semantic data presenting impressive results for the coherence, speed and precision.

Keywords: semantic analysis, factorial analysis, dimension reduction, penalized logistic regression

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951 Awareness of Organic Products in Bangladesh: A Marketing Perspective

Authors: Sheikh Mohammed Rafiul Huque

Abstract:

Bangladesh since its inception has been an economy that is fuelled by agriculture and agriculture has significant contribution to the GDP of Bangladesh. The agriculture of Bangladesh predominantly and historically dependent on organic sources of raw material though the place has taken in decades by inorganic sources of raw materials due to the high demand of food for rapidly growing of population. Meanwhile, a new market segment, which is niche market, has been evolving in the urban area in favor of organic products, though 71.1% population living in rural areas is dependent mainly on conventional products. The new market segment is search of healthy and safer source of food and they could believe that organic products are the solution of that. In Bangladesh, food adulteration is very common practices among the shop-keepers to extend the shelf life of raw vegetables and fruits. The niche group of city dwellers is aware about the fact and gradually shifting their buying behavior to organic products. A recent survey on organic farming revealed that 16,200 hectares under organic farming in recent time, which was only 2,500 hectares in 2008. This study is focused on consumer awareness of organic products and tried to explore the factors affecting organic food consumption among high income group of people. The hypothesis is developed to explore the effect of gender (GENDER), ability to purchase (ABILITY) and health awareness (HEALTH) on purchase intention (INTENTION). A snowball sampling was administered among the high income group of people in Dhaka city among 150 respondents. In this sampling process the study could identify only those samples who has consume organic products. A Partial Least Square (PLS) method was used to analyze data using path analysis. It was revealed from the analysis that coefficient determination R2 is 0.829 for INTENTION endogenous latent variable. This means that three latent variables (GENDER, ABILITY, and HEALTH) significantly explain 82.9% of the variance in INTENTION of purchasing organic products. Moreover, GENDER solely explains 6.3% and 8.6% variability of ABILITY and HEALTH respectively. The inner model suggests that HEALTH has strongest negative effect on INTENTION (-0.647) followed by ABILITY (0.344) and GENDER (0.246). The hypothesized path relationship between ABILITY->INTENTION, HEALTH->INTENTION and GENDER->INTENTION are statistically significant. Furthermore, the hypothesized path relationship between GENDER->ABILITY (0.262) and GENDER->HEALTH (-0.292) also statistically significant. The purpose of the study is to demonstrate how an organic product producer can improve his participatory guarantee system (PGS) while marketing the products. The study focuses on understanding gender (GENDER), ability (ABILITY) and health (HEALTH) factors while positioning the products (INTENTION) in the mind of the consumer. In this study, the respondents are found to care about high price and ability to purchase variables with loading -0.920 and 0.898. They are good indicators of ability to purchase (ABILITY). The marketers should consider about price of organic comparing to conventional products while marketing, otherwise, that will create negative intention to buy with a loading of -0.939. Meanwhile, it is also revealed that believability of chemical free component in organic products and health awareness affects health (HEALTH) components with high loading -0.941 and 0.682. The study analyzes that low believability of chemical free component and high price of organic products affects intension to buy. The marketers should not overlook this point while targeting the consumers in Bangladesh.

Keywords: health awareness, organic products, purchase ability, purchase intention

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950 Terrain Classification for Ground Robots Based on Acoustic Features

Authors: Bernd Kiefer, Abraham Gebru Tesfay, Dietrich Klakow

Abstract:

The motivation of our work is to detect different terrain types traversed by a robot based on acoustic data from the robot-terrain interaction. Different acoustic features and classifiers were investigated, such as Mel-frequency cepstral coefficient and Gamma-tone frequency cepstral coefficient for the feature extraction, and Gaussian mixture model and Feed forward neural network for the classification. We analyze the system’s performance by comparing our proposed techniques with some other features surveyed from distinct related works. We achieve precision and recall values between 87% and 100% per class, and an average accuracy at 95.2%. We also study the effect of varying audio chunk size in the application phase of the models and find only a mild impact on performance.

Keywords: acoustic features, autonomous robots, feature extraction, terrain classification

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949 Sixth-Order Two-Point Efficient Family of Super-Halley Type Methods

Authors: Ramandeep Behl, S. S. Motsa

Abstract:

The main focus of this manuscript is to provide a highly efficient two-point sixth-order family of super-Halley type methods that do not require any second-order derivative evaluation for obtaining simple roots of nonlinear equations, numerically. Each member of the proposed family requires two evaluations of the given function and two evaluations of the first-order derivative per iteration. By using Mathematica-9 with its high precision compatibility, a variety of concrete numerical experiments and relevant results are extensively treated to confirm t he t heoretical d evelopment. From their basins of attraction, it has been observed that the proposed methods have better stability and robustness as compared to the other sixth-order methods available in the literature.

Keywords: basins of attraction, nonlinear equations, simple roots, super-Halley

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948 Adapted Intersection over Union: A Generalized Metric for Evaluating Unsupervised Classification Models

Authors: Prajwal Prakash Vasisht, Sharath Rajamurthy, Nishanth Dara

Abstract:

In a supervised machine learning approach, metrics such as precision, accuracy, and coverage can be calculated using ground truth labels to help in model tuning, evaluation, and selection. In an unsupervised setting, however, where the data has no ground truth, there are few interpretable metrics that can guide us to do the same. Our approach creates a framework to adapt the Intersection over Union metric, referred to as Adapted IoU, usually used to evaluate supervised learning models, into the unsupervised domain, which solves the problem by factoring in subject matter expertise and intuition about the ideal output from the model. This metric essentially provides a scale that allows us to compare the performance across numerous unsupervised models or tune hyper-parameters and compare different versions of the same model.

Keywords: general metric, unsupervised learning, classification, intersection over union

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947 Aircraft Pitch Attitude Control Using Backstepping

Authors: Labane Chrif

Abstract:

A nonlinear approach to the automatic pitch attitude control problem for aircraft transportation is presented. A nonlinear model describing the longitudinal equations of motion in strict feedback form is derived. Backstepping is utilized for the construction of a globally stabilizing controller with a number of free design parameters. The controller is evaluated using the aircraft transportation. The adaptation scheme proposed allowed us to design an explicit controller with a minimal knowledge of the aircraft aerodynamics. Finally, the simulation results will show that backstepping controller have better dynamic performance, simpler design, higher precision, easier implement, etc. At the same time, the control effect will be significantly improved. In addition, backstepping control is superior in short transition, good stability, anti-disturbance and good control.

Keywords: nonlinear control, backstepping, aircraft control, Lyapunov function, longitudinal model

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946 A New Framework for ECG Signal Modeling and Compression Based on Compressed Sensing Theory

Authors: Siavash Eftekharifar, Tohid Yousefi Rezaii, Mahdi Shamsi

Abstract:

The purpose of this paper is to exploit compressed sensing (CS) method in order to model and compress the electrocardiogram (ECG) signals at a high compression ratio. In order to obtain a sparse representation of the ECG signals, first a suitable basis matrix with Gaussian kernels, which are shown to nicely fit the ECG signals, is constructed. Then the sparse model is extracted by applying some optimization technique. Finally, the CS theory is utilized to obtain a compressed version of the sparse signal. Reconstruction of the ECG signal from the compressed version is also done to prove the reliability of the algorithm. At this stage, a greedy optimization technique is used to reconstruct the ECG signal and the Mean Square Error (MSE) is calculated to evaluate the precision of the proposed compression method.

Keywords: compressed sensing, ECG compression, Gaussian kernel, sparse representation

Procedia PDF Downloads 450